Within the past decade, several technologies have made it possible to monitor the expression level of a large number of transcripts within a cell at any one time (see, e.g., Schena et al., 1995, Quantitative monitoring of gene expression patterns with a complementary DNA micro-array, Science 270:467–470; Lockhort et al., 1996, Expression monitoring by hybridization to high-density oligonucleotide arrays, Nature Biotechnology 14:1675–1680; Blanchard et al., 1996, Sequence to array: Probing the genome's secrets, Nature Biotechnology 14, 1649; 1996, U.S. Pat. No. 5,569,588, issued Oct. 29, 1996 to Ashby et al. entitled “Methods for NY2-1221902.1 Drug Screening”). In organisms for which the complete genome is known, it is possible to analyze the transcripts of all genes within the cell. With other organisms, such as human, for which there is an increasing knowledge of the genome, it is possible to simultaneously monitor large numbers of the genes within the cell.
Early applications of this technology have involved identification of genes which are up regulated or down regulated in various diseased states. Additional uses for transcript arrays have included the analyses of members of signaling pathways, and the identification of targets for various drugs. However, because proteins are regulated by many different processes that include, not only transcription, but also translational controls and post-translational controls, it has not previously been recognized that transcript arrays might be beneficial in analyzing differential activity of proteins.
However, the ability to monitor minor differences in protein activity levels would be of great human and commercial value. For example, most genetic mutations that produce a diseased state do so by disrupting the activity level of the corresponding gene product. Thus, the ability to determine disruption or partial disruption of activity of a particular gene product, i.e., a particular protein, in cells provides a useful means for identifying those individuals having genetic mutations and/or polymorphisms that disrupt the function of important proteins. In particular, there are numerous cancer susceptibility genes, numerous genes that determine metabolism of drugs, and genes that determine the presence of numerous disease states which, if altered in one of the two alleles, would provide an increased risk for a large set of health related problems. Examples of such genes, which are referred to herein as “susceptibility genes”, include, but are not limited to, BRCA1 and BRCA2, which are associated with greatly increased susceptibility to breast and ovarian cancer (Cannon-Albright and Skolnick, 1996, Seminars in Oncology 23:1–5), APC which is associated with an increased susceptibility to colon cancer (Tomlinson et al., 1997, Cancer and Metastasis Reviews 16:67–79; and Cunningham and Dunlop, 1996, British Journal of Surgery 83:321–329), p16/CDKN2A which is associated with an increased susceptibility to cutaneous melanoma (Haluska and Hodi, 1998, Journal of Clinical Oncology 16:670–682), RET and VHL which are associated with an increased susceptibility to pheochromocytoma and hypertension (Hartmut et al., 1996, American Journal of Kidney Diseases 28:329–333), AT1R which is associated with diabetic nephropathy (Chowdhury et al., 1997, Diabet. Med. 14:837–840), IRS1 which is associated with type II diabetes (Stern et al., 1996, Diabetes 45:563–568), apoE which is associated with Alzheimer's disease (Weisgraber and Mahley, 1996, FASEB J. 10:1485–1494), and p53 which is associated with several types of human cancers (see, e.g., Friend, 1994, Science 265:334–335; Frebourg and Friend, 1992, J. Clin. Invest. 90:1637–1641; and Li et al., 1992, J. Natl. Cancer Inst. 84:1156–1160). For a review of polymorphisms that affect drug metabolism in humans see, e.g., Smith et al., 1995, Cancer Surveys, vol. 25: “Genetics and Cancer: A Second Look”, Imperial Cancer Research Fund.
In particular, there is a need for methods for identifying individuals having heterozygous mutations, i.e., mutations in which one of the two alleles of a gene is altered. Direct detection of heterozygous mutations is problematic with PCR since the wild type copy of the gene is also present. Further, the exact sequence of the mutated gene copy will not, in general, be known. Additionally, the genotype of a mutation is not as direct an indication of protein function as are the effects of the protein itself. Consequently, the monitoring of protein function is often a superior indicator of a disease state or disease susceptibility compared to genotyping, since the protein activity level is more directly related to organism function (see, e.g., Brown and Hartwell, 1998, Nature Genetics 18:91-93). Direct monitoring of protein function in heterozygote carriers is ofter difficult, however, because assays are complex and monitoring of 50% or less decrease in overall activity can be difficult biochemically.
Methods for analyzing differential function of proteins would also be useful to monitor the activity of drugs in cells, in vivo. Currently, it would be a great benefit if one could assay for diminished activities that drugs have over time in a way that is not dependent upon independently characterizing individual metabolic breakdown products.
Thus, there is a need for methods of monitoring the activity levels of proteins in cells. In particular, there is a need for methods for monitoring protein activity in cells which thereby make it possible to identify individuals who have genetic mutations and/or polymorphisms that disrupt the activity of important proteins, and are associated with diseased states or with an increased susceptibility to certain diseased state. Further, there is a need for methods of monitoring protein activity in cells which allow for identifying the activity of drugs in vivo.
Discussion or citation of a reference herein shall not be construed as an admission that such reference is prior art to the present invention.